AFRL/RY Wright-Patterson Air Force Base, Ohio

SF.35.01.B0118: Solid-State Laser Source Development

(937) 713-8658

We investigate and develop new infrared (1.5-12 μm) materials, devices, and technologies that have potential for high lasing efficiency, broad wavelength tunability, and robust operation. Research includes exploration and development of new solid-state laser media such as Cr2+ doped into ZnSe and analogous semiconductor host materials. Lasers with direct emission throughout the infrared spectrum and room-temperature operation are sought. Current projects include demonstration of high-power modelocking, Q-switching and CW operation of Cr2+:ZnSe, demonstration of sub-ns pulse operation of a Tm μ-chip oscillator-fiber amplifier, and demonstration of > 2-μm fiber lasers. Rapid tuning, beam control via guiding structures, and beam switching are also performance issues. Infrared lasers (bulk, fiber, and semiconductor types) are also being developed for use as pumps of new quasi-phasematched nonlinear media such as orientation patterned gallium arsenide. Areas of interest include spectroscopy of infrared laser materials, beam transport in infrared fibers and waveguides, and infrared nonmechanical beam steering. Facilities are available to perform spectroscopic measurements of absorption, excited-state absorption, fluorescence, fluorescence lifetime, and ultrashort pulse characterization. A variety of pump lasers are available including Nd:YAG lasers, Tm fiber lasers, Tm,Ho:YLF Q-switched lasers, and semiconductor lasers for measuring spectral content, power, beam quality, and thermo-optic properties of new laser materials.

(2) Eye-safe transmitters for coherent laser radar. The objective is to develop efficient laser-based systems capable of gathering multidimensional images, where the dimensions can include spatial (x,y,z), spectral, polarization, and vibration characteristics. Transmitters with agile wavelength and with waveform agility are desirable, as they can be used for multiple imaging modes. Transmitters need to be capable of high peak powers with minimal stimulated Brillouin scattering effects for continuous wave and especially pulsed applications.

(3) Shot noise limited coherent receivers for laser radar. Full waveform reception multi-mode laser radar signals are desired. Also of interest are techniques which can help to implement conformal/distributed coherent apertures, including non-mechanical beam steering and photonic integrated circuits among others. Receive apertures that can be used for transmitting or passive imaging at other wavelengths as well are preferable due to the increased functionality.

SF.35.01.B4960: Advanced Digital Receiver/Aperture Development

(937) 713-8553

Our ultimate goal is to realize fully digital multifunction active arrays with programmable functionality. In this architecture, only the high power and low noise amplifiers at the aperture are analog circuits. Wide-bandgap semiconductors are candidates for these high-power and linear amplifiers. All the amplitude and phase-shifting functions, as well as the beam-forming, are done digitally. Transmit waveforms are generated by direct digital synthesizers and the received signals are captured with very high-speed analog-to-digital converters with deep dynamic range and wide frequency response. True time delay for steering very large wideband agile arrays is also digitally implemented. This architecture requires very high-speed, high-throughput data processing. Commercial simulation tools can facilitate the design of the array aperture and radiators, as well as the components used in the active phased array. Behavioral simulation methodology allows performance prediction of experimental components used in the architecture. Affordability, size, and power consumption are important factors to include in the trade space, but may be considered secondary to advanced performance capabilities. Military RF sensors must operate in extremely dense signal environments (including intentional, unintentional, and co-channel interfering signals). UHF and VHF radars for Foliage Penetration and ground penetration are especially vulnerable because of the dense array of commercial emitters, limited aperture spatial discrimination, wide instantaneous bandwidths, and long integration times required. Research in all areas of RF system design mentioned above is sought.

SF.35.01.B5814: Precision Navigation Reference Sensor Techniques

(937) 713-4413

Our goal is to research and develop the latest technologies to provide precise Postion, Navigation, Attitude, and Time (PNAT) for military systems operating in any environment at any time. PNAT is the cornerstone in providing an assured reference for distributed sensing and warfare. Research includes investigating inertial sensor technologies and their integration with secondary sensors (preferably passive) that provide precision measurement updates, as well as optimization of the reference solution for the specific distributed or staring sensing task. Potential secondary sensors include jam resistant global positioning system (GPS) technologies, optical sensors using passive image data, light detection and ranging (LIDAR) sensors using ranging data, and software based receivers and navigation using natural signals (e.g., the Earth’s magnetic field).

Current in-house research partially focuses on exploration of military use of global navigation satellite systems (GNSS) and sensor-inertial fusion in constrained environments where GPS may not be available. A critical piece of this research effort involves determining the optimal method for integrating various navigational aiding sensor data into a precision navigation system.

(937)-713-8709

With the increasing proliferation of tightly integrated digital control algorithms, sensors and actuators, and corresponding circuitry, reconfigurable/multifunction RF circuit components are viewed as enabling components for future autonomous systems. Future system applications in contested environments depend on the capability to sense, learn and adapt in real time based upon mission and environmental factors. Envisioned transmitter operating conditions and scenarios will certainly require differing metrics with regard to frequency, bandwidth, gain, output power, transmitted noise levels, linearity, efficiency, and peak-to-average power ratio (PAPR). For receivers, the ability to negate unwanted jamming signals, in addition to frequency, bandwidth, gain, noise levels, linearity, dynamic range, DC power consumption and survivability are important parameters that can be traded off depending on the scenario.

To this end, research focuses on enabling components and techniques for autonomous front-ends. Waveform and frequency agility are desired characteristics. For transmitters, maintaining efficient operation is vital for reducing thermal constraints and prime power requirements. For receivers, the ability to operate in the presence of jamming signals would be advantageous. Potential topic areas of interest include, but are not limited to, novel architectures, switching elements, signal injection/cancellation techniques, sensors, actuators, control algorithm implementation, and modeling at both the device and system sub-system level.

SF.35.01.B6349: Radio Frequency Micro-electromechanical System Design, Fabrication, Packaging, and Characterization

(937) 713-8698

Micro-electromechanical systems (MEMS) switches offer numerous advantages for radio frequency (RF) systems over competing technologies. Several MEMS technology advantages include low insertion loss, high linearity, and reduced size. Although the reliability of RF MEMS devices has improved dramatically over the last several years, deficiencies in several fundamental areas associated with the technology persist. Areas that we are currently working on include (1) wafer-level encapsulation of the switches, (2) dielectric charging characterization, and (3) metal contact damage evolution. Wafer-level thin-film encapsulation provides discrete device packaging to protect the switches from the environment. Current research efforts focus on the sealing of thin-film encapsulants and characterization of the package hermeticity. The electrical performance and reliability of RF MEMS capacitive switches is dependent on the properties of the switch’s dielectric material. We are conducting experiments to quantify the charging and discharging behaviors of the dielectric materials for capacitive switches. We are also interested in modeling the contact wear mechanics of the mating surfaces for metal contact MEMS switches. Model validation is anticipated through examination and testing of fabricated devices. Device processing and test facilities are available to fabricate and characterize the RF MEMS switches. Device fabrication is completed in an on-site clean room facility. RF probe stations and an environmental chamber are used for electrical characterization and hermeticity experiments.

SF.35.01.B6350: Investigation and Optimization of Existing and Novel Electronic Devices

(937) 713-8877

The goal of this project is to investigate and optimize the electrical performance of existing devices, devising and investigating novel electronic devices (e.g.,nanoelectronic devices). Investigation of these devices through electrical characterization, limited physical characterization, and modeling will enable a better understanding of their limitation and potential. The information produced in this project will push the limits of the current state-of-the-art in electronics.

An example of this research includes, but is not limited to, the optimization of AllnN/GaN HEMTs by investigating changes in electrical device performance due to changes in device fabrication. For this example, components that could be studied are silicon nitride dielectric passivation, ohmic and Schottky contact formation with variations in metal stack components, and surface treatments prior to metal deposition.

SF.35.01.B6351: Multichannel Radio Frequency Sensor Processing

(937) 713-8727

We develop radio frequency sensor processing hardware and software techniques. The use of multiple channels on transmit and receive enables multiple Degrees of Freedom (DOF) processing and Digital Beam-Forming (DBF). Research interests fall into the following categories:

(1) Novel multichannel architectures. The goal is to achieve broad spatial and frequency coverage utilizing multiple simultaneous beams. Architectures should be scalable in number of channels and capability (number of beams, bandwidth coverage).

(3) Software compensation schemes. Many multichannel signal processing techniques assume perfectly matched hardware channels. It is desirable to have digital/software compensation schemes that correct for mismatches, or to develop processing techniques that are impervious to channel mismatch. We are interested in research in compensation schemes for Analog (Amplifiers, mixers, transmission lines), and mixed signal (Analog-to-digital Converter) component non-linearity, as well as inherently robust processing algorithms.

SF.35.01.B6593: Nonlinear Optical Materials and Devices

(937) 713-8657

We investigate and develop new nonlinear optical devices, primarily for frequency conversion applications. Specifically we are seeking tunable coherent sources in the mid-infrared (2-5 micron) and far-infrared (8-12 micron) spectral regions. We are also interested in beamsteering, modulation, and other techniques that improve the performance and utility of frequency conversion devices. Current projects focus on quasi-phasematched (QPM) materials, specifically orientation-patterned semiconductors, in both bulk and waveguide form; although other QPM materials, innovative birefringently-phasematched crystals, and techniques for enhancing performance in more established materials are also of interest. Experiments address optical characterization of candidate materials, demonstration and performance characterization of nonlinear devices, and performance modeling, with the goal of improving material fabrication processes and device designs to optimize performance. Facilities are available for measuring absorption, fluorescence, and scatter, as well as thermo-optical properties. A variety of lasers are available for use both in material characterization and as pump sources for frequency conversion and other nonlinear devices. Optical parametric oscillator testbeds are available, along with equipment for measuring device output power, spectral content, beam quality, and other performance parameters. AFRL also has a class 100 clean room and facilities for fabricating periodically poled ferroelectric materials, for bonding semiconductors and other optical materials, and for MBE growth of GaAs.

SF.35.01.B6878: Infrared Sensing Research

(937) 713-8831

(1) Hyperspectral Imaging. This area includes both imaging spectrometer instrumentation for remote sensing and signal processing algorithms for material detection, tracking, identification, and characterization. Novel imaging spectrometer designs that achieve excellent spectral resolution, field-of-view, and radiometric sensitivity in the visible through longwave infrared spectral region are being pursued. We are particularly interested in compact longwave infrared spectrometer designs that achieve high throughput and wide field-of-view. Signal processing advances are investigated for low contrast target detection in diverse clutter backgrounds, change detection over large environmental variations, material identification based on radiometric target/background models.

(2) Long Range Air-to-Ground Imaging. This area includes optical hardware and signal processing concepts for greatly enhancing image quality at very long ranges, including both visible and infrared spectral regions. Issues of particular interest include compensation of long path air-to-ground turbulence effects, imaging through distributed scattering media, shortwave infrared imaging technology, resolution enhancement processing, and unconventional imaging techniques such as passive interferometric and sparse aperture imaging to achieve sub-diffraction-limited spatial resolution.

(3) Infrared Focal Plane Arrays. This area includes theoretical and experimental research enhancing the performance of focal plane arrays in the shortwave to longwave infrared spectral regions for electro-optical and infrared systems. Particular interests include investigation of III-V superlattice and heterostructure materials to maintain low dark current at high operating temperatures, new detector materials that simplify hybridization with silicon readout circuits (ROICs), and novel analog and digital ROIC designs that enhance sensing capability.

SF.35.01.B0315:Vehicle Vibration Signature Exploitation

(937) 713-4378

AFRL is interested in the study of Aided Target Recognition (AiTR) algorithms by knowing the dependence on target characteristics and the sensor parameters to enable the researcher a better understanding of the constraints on detection performance. AiTR algorithm performance is sensitive to variability in the observed target signature. Algorithms are developed and tested under a specific set of operating conditions and then are often required to perform well under very different conditions (referred to as Operating Conditions, or OCs). The stability of the target signature as the operating conditions change dictates the success or failure of the recognition algorithm. Laser vibrometry is a promising sensor modality for vehicle identification. Identifying vehicle features such as engine type, speed, and number of cylinders from vibrometry data provides significant context in a variety of commercial and military applications. The AiTR task is to analyze the vibration spectral signature to determine what type of vibration sources the vehicle contains, thereby identifying the vehicle type. In many cases, potential targets can be reliably identified by their engine vibration signatures. This effort may include a data collection using fixed sensors. In addition to publications (both on ATRPedia and public sources), delivery of documented source code will be expected.

(937) 713-8853

Applications in active sensors and infrared countermeasures may often be significantly improved by unique sources. We theoretically and experimentally investigate high-brightness semiconductor lasers with unique properties such as broad tunability, mid-wave and long-wave operation, fast modulation, and multi-wavelength operation. Devices such as vertical external cavity surface emitting lasers combine the inordinate semiconductor optical gain with a classic macroscopic laser cavity, which results in a device that can achieve signal spatial-mode operation under many watts of optical output powers approaching in any wavelength achievable by semiconductor lasers. We are interested in longer wavelength semiconductor lasers in uncommon operation regions, such as the 2-4-micron band through interband Type-I and Type-II lasers, large conduction-band offset intersubband lasers. It is essential to understand material systems (such as GaAs- and GaSb-related compounds) to appropriately design a laser cavity. For example, Auger recombination and carrier confinement both become extremely influential at high power and temperatures. Mitigation of these deleterious effects is essential for efficient operation.

Interest areas include material design and development, fabrication, coupled resonator designs, passive mode-locked lasers, spatial temporal waveform generation schemes for semiconductor lasers, as well as nonlinear frequency conversion. Fabrication facilities are available including semiconductor growth, typical microfabrication techniques, electron-beam lithography, as well as numerous metal and dielectric film deposition techniques. A full testing capability suite is available for cryogenic through high-temperature measurements for device operation.

(937) 713-8920

The major objectives of this work are to design, simulate and fabricate plasmonic and micro-/nano-resonant structures and devices for optical and photonics sensing applications. Examples of such structures may include metallic media, semiconductor patterned structures, Fano-resonant antennas, plasmonic metamaterials, or resonant nanocavities. Theoretical models and computational simulations will be developed for these structures to describe the electromagnetic behavior as well as to optimize these devices. The resulting fabrication techniques and modeling methods will lead to new technology for devices that can be tailored for specific sensing schemes for optical signal enhancement and detection. It is anticipated that the modeling/fabrication/characterization efforts will be iterative towards the development of a highly sensitive optical sensing platform that is robust and wavelength scalable.

(937) 713-8310

Electronic warfare (EW) receiver is a unique receiver that detects unknown radar signals in a real-time situation. EW wideband digital receiver contains a front analog subsystem and a back digital subsystem. Much effort has been done to improve the performance of the front subsystem. The digital subsystem usually includes time-frequency transfer and signal detection encoder. We are interested in the development to achieve an overall EW receiver performance. Several topics are under consideration:

(1) Innovative method to improve sensitivity in single signal detection and dynamic range in two-signal detection. Understanding and effective modeling of the nonlinear effects due to the analog components in the front subsystem is the first step. The efficient algorithm may then be developed to compensate the effect. The algorithm is preferable to be adaptive and in real-time.

(2) There are various filter bank designs to track wideband signals. Are there optimized filter design and encoder algorithm to effectively detect multiple signals simultaneously? Understanding the fundamental limitation such as the time and frequency resolutions, and the current specifications of the target signal is the first step. The ringing (rabbit ear) effect due to the pulse edges may impose performance limitation with filter bank design.

(4) Multiple-channel receiver testbed is available in our laboratory. Research topics on various issues involved in digital beam forming techniques such as channel imbalance and mitigation, beam pattern formation, direction finding, compressive sensing methodology, time synchronization among multiple platforms, etc., are of interest.

This research effort includes the model development, followed by numerical simulation to prove the feasibility of algorithm. Preferably, the development can be validated by hard/firmware implementation.

(937) 713-8886

Our research focuses on the development of oxide materials and the incorporation of these oxide materials in high performance transistor applications. Current investigations include beta-Ga2O3 MOSFETs, ZnO and InGaZO thin film transistors, and impurity doped ZnO thin films for transparent conductors.

(937) 713-8574

Recent advances in mathematical modeling include the development of novel models for knowledge representation and reasoning based on category theory (e.g., the work of Spivak on OLOGS) and the emerging field of homotopy type theory. Incorporating uncertainty modeling into these abstract models is important for these methods to be useful for Air Force layered sensing applications, but this requires generalizations of classical probability theory. We seek theoretical advances and tractable, implementable algorithms for modeling and reasoning with uncertainty in abstract relational mathematical models that can be used to support situational representation and understanding. Publication of the resulting work (both on ATRPedia and in public sources) is expected, along with the delivery of any source code developed.

SF.35.01.B7062: Distributed Netted Radar Signal Processing

(937) 713-8124

Research opportunities exist in distributed, netted radar systems for detecting difficult (low cross section, low Doppler) targets embedded in severe clutter backgrounds. A distributed network of radars systems, including multiple input multiple output (MIMO), consists of multiple radar stations netted together through data communication links. Traditional netted radar systems normally comprise several monostatic radar systems, each operating at a different carrier frequency to avoid the interference and detection confusion among the radar stations in the system. As a result, the multiple radar stations in the system are incapable of operating in a bistatic or a multistatic mode. The strong capabilities of bistatic and multistatic radar systems are well known. An improved netted radar system is one that can simultaneously operate in both bistatic and monostatic modes. In this case, all radar stations are assumed to operate at the same carrier frequency and are coordinated and controlled by a coherent, signal-level fusion processing unit. Such a system not only significantly improves radar performance in target search, tracking, and recognition, but also effectively addresses emerging radar challenges. However, many fundamental challenges exist and need to be addressed. We seek novel methods of waveform design (specifically orthogonal or quasi-orthogonal waveforms) for proper radar functioning. New and robust adaptive processing techniques capable of operating in both bistatic and multistatic environments are also sought. For airborne and spaceborne applications, the geometry-induced Doppler dispersion significantly degrades the performance of adaptive processing techniques such as Space-Time Adaptive Processing (STAP). Multistatic clutter characterization techniques are also desired for better understanding of the impact of clutter on detection performance in these environments. Finally, depending on whether all data is sent to the fusion processing unit for detection purposes (centralized processing), or individual detections made at the sensor level are sent to the fusion center (decentralized processing), new signal processing techniques are desired that cohere signals across multiple distributed radar apertures.

SF.35.01.B7063: Computational Physics for Radar Signal Processing

(937) 713-8569

Research opportunities exist in computational science to design, implement, and test algorithms for enhanced radar designs. Advances in radar signal processing techniques are increasingly using the physical details of the signal environment. We are particularly interested in advancing novel computational electromagnetic algorithms for use on the most challenging radar problems. These challenges include using radio frequency signals for underground sensing as well as for sensing applications throughout the ionosphere.

SF.35.01.B7107: Computational Electromagnetics and Electronics

(937) 713-8191

This research involves topics in computational electromagnetics and charge thermodynamics-treated both separately and as a fully coupled system. By itself, the electromagnetics component emphasizes efficient full wave methods for electrically large linear problems. Domain decomposition algorithms applied to full wave discretization schemes are considered along with sufficiently accurate field expansion approximations. Applications for these approaches include optical cavities, waveguides, and nanophotonics. The electronics component focuses on charge transport, particularly in the Fermi gas/drift-diffusion approximation. Accurate representation of hot electron effects and the role of semiconductor bandstructure within this formalism are of interest, as well as the coupling of the classical and quantum confined regions of quantum devices. Applications include quantum well and quantum cascade lasers, detectors, and wide bandgap HFETs. Research interests in such opto- and micro-electronic components extend to high frequency wave effects requiring a fully coupled treatment of vector field electromagnetics and charge dynamics.

(937) 713-8711

Quantum encoding photons and entanglement are non-classical features unique to interacting quantum systems and are considered to be the fundamental resources that underlie the power of quantum computation, quantum communication, and quantum memory and storage. In general, quantum information processing can be considered as the exploitation of engineered quantum systems. Our goals are to exploit quantum encoded photons and entanglement for the purpose of developing quantum information processing systems with the potential to exceed conventional computing capabilities. Quantum computing systems with unprecedented levels of security and computational capability for select applications promise decreased computation times for complex AF problems such as faster optimization of complex AF C2 systems, ultrahigh-speed signal and image processing, and informational data base searches with a quadratic speed-up.

Current research focuses on the development of photonic integrated circuits that will enable the processing of quantum encoded photons and entangled photon pairs with significantly scaled down dimensions from table top experiements. Generation of single and entangled photons, coupling them into photonic waveguides and devices with polarization maintaining and low optical lossess are of interest.

SF.35.01.B7313: Waveform Agile Radar Processing (WARP)

(937) 713-8567

Radar systems transmit an electromagnetic signal into a volume of space containing both objects of interest (targets) and objects not of interest (clutter). The signal reflects from both kinds of objects and these reflections are received by the radar along with signals produced by other sources (interference). The radar must then separate the target returns from the clutter and interference. There are currently effective techniques for adaptively suppressing clutter and interference at the receiver. Salient examples include constant false alarm rate (CFAR) detectors, adaptive antenna beam forming techniques, and space-time adaptive processing (STAP). In theory, clutter and interference suppression could be enhanced if the transmit signal was tailored to the target/clutter/interference environment. However, despite potentially significant performance gains, this kind of transmit adaptivity has not yet become a mature technology. This is principally due to the insufficient computing power and limited RF waveform generation hardware that have rendered adaptive transmit techniques impractical to implement. However, the coupling of Moore’s Law with recent advances in arbitrary waveform generation has dramatically improved the prospects of transmit adaptivity as a viable technology. We say that a system is "transmit adaptive" if it is capable of altering its transmit waveform in response to knowledge about its environment. By "environment" we mean those elements that affect system performance, such as targets, clutter, and radio frequency interference (RFI). Knowledge of the environment could be acquired a priori, estimated online, or both. There are three main reasons to investigate transmit adaptivity in radar systems: (1) performance improvement, (2) resource management, and (3) novel missions. The first reason involves improving performance subject to constraints on the transmit waveform (e.g., peak power, nice autocorrelation); the remaining two reasons focus on maintaining a minimum level of performance while either minimizing resources or performing multiple functions. For example, a transmit-adaptive system might be able to compute a transmit waveform that maximizes the probability of detection in a given RFI environment (Reason 1). Such a system might also be able to maintain the probability of detection at a desired level while using a minimal amount of transmitted power and bandwidth (Reason 2). Efficient spectrum usage afforded by such a system would provide an immense benefit in a spectrally congested environment. Ideally, an ATx system would also be capable of performing two missions simultaneously--e.g., spotlight synthetic aperture radar (SAR) and digital communications--while maintaining a minimum level of performance for each function (Reason 3). The multifunction capability afforded by WARP would be of considerable benefit in realizing one or more attributes of the Layered Sensing paradigm. Research opportunities exist in every aspect of waveform design and optimization. This includes theoretical design of waveforms, optimization algorithms, and efficient computation. Transition opportunities to investigate practical aspects of implementation and proof of concept demonstrations are available through other laboratory resources.

SF.35.01.B7326: Ultra-Sensitive Receiver Architectures

(937) 713-8248

Comprehending the physics-based relationship between a receiver noise floor and sensitivity, parameters such as temperature and bandwidth should offer a multi-dimensional representation of signal to noise (SNR) dynamic range, and in the case of complex signals of interest, instantaneous dynamic range (IDR). This is often defined as the measurement of a weak signal in the presence of a strong one or as a signal buried far below a dense RF interference background. Innovations in receiver architectures will be required as well as novel methods for characterizing signals as a function of energy, time and frequency separation. Design of Experiments using physical modeling and simulation tools is desired in developing the RF receiver architectures and appropriate statistical analysis. The formulation of RF laboratory experiments for prototyping of ultra-sensitive receiver sub-systems integrated with beam-forming antenna/aperture assemblies for future defense applications. Recently completed research at AFRL has revealed opportunities for the development of non-traditional RF receiver architectures which bridge quantum physics and RF technologies (micro/nano-electronics, superconductors, photonics and meta-materials) as a multidisciplinary area to address fundamental limitations (e.g., sampling jitter, thermal noise, Nyquist/Shannon theorem limitations) to more efficiently convert a signal from the RF to an encoded digital format. The long-term research goal is to enable an RF receiver capable of simultaneous search and analysis modes under dense/complex signal conditions enable revolutionary sensor payloads.

SF.35.01.B7367: Computational Methods for Antenna Designs

(937) 713-8913

This opportunity involves the application of advanced numerical methods for computational electromagnetics towards the modeling of antenna systems. Methods of interest include finite element tearing and interconnect (both time and frequency domain methods), time domain boundary integral methods, and Discrete Galerkin methods. These numerical methods are to be utilized on high performance parallel computers with distributed memory architectures. Applications of interest include antennas on platforms, large phase array antennas, wideband antennas, and conformal antennas. These techniques are to be applied to electrically large systems with the goal of obtaining accurate solutions for multiscale and highly heterogeneous structures. Balancing the burden between user inputs, meshing, and computers to obtain idealized throughput for design studies is also a desired goal.

(937) 713-8851

This research primarily focuses on manipulating light within laser cavities in order to generate diverse waveforms outside of the laser. Work is currently being conducted experimentally by investigating the mode locking and modulation of multi-section quantum-dot lasers. Computationally we are solving systems of partial differential equations based on traveling-wave models which are able to incorporate not only carrier dynamics but spatial effects in the cavity. We have found that the use of delay differential equations provides a compact model still able to capture some spatial effects and our analytical work has focused on this type of model. Opportunities exist to contribute to one or more of the above listed areas depending on one’s background and interest level.

SF.35.01.B1528: Active Electro-Optical Automatic Target Recognition

(937) 713-8290

Description: Recent advances in airborne synthetic aperture lidar (SAL) systems have allowed for the collection of higher-resolution 2D/3D images and point clouds from longer stand-off ranges. This technology is highly beneficial for operations in denied environments but currently has a need for advanced automatic target recognition (ATR) and classification algorithms. This topic seeks to develop effective algorithms for advanced ATR and classification for active electro-optical sensors (i.e. Laser radar, SAL, etc.). Data can be provided and delivery of any developed source code is expected.

(937) 713-8184

State estimation lies at the heart of most dynamic or reasoning systems. As these systems have become more complex, state estimators have advanced from the early Kalman filter implementations to estimators that handle larger and more complex state vectors (including mixed discrete and continuous states), accept significantly non-linear dynamic and measurement models, and handle more complicated probability distributions.

In addition to these improvements in estimators, we are particularly interested in new estimation algorithms and approaches that address the following problems:

1. Estimators that produce accurate uncertainty estimates. Much work on making better estimators has focused on computing the most accurate state estimate possible given the observed data. In many applications though, the uncertainty associated with that state estimate is of equal import to the state estimate itself. Therefore, we are interested in improvements to estimation algorithms that yield more accurate uncertainty estimates of the estimated state. One area of particular interest are computer vision algorithms where the inputs have large number of outliers. While algorithms have long been used to screen out these outliers, these algorithms’ effects on the uncertainty outputs of the estimators is not well understood or characterized.

2. Self-tuning estimators that can adjust to different uncertainties on the input signals. For example, a navigation estimator that takes in both GPS (global positioning system) and inertial measurement unit (IMU) inputs is typically tuned to the performance of a specific IMU. However, even when an IMU of the same series is put into the system, its measurements may have different uncertainty characteristics than the unit that the GPS/IMU estimator was tuned for. This can have significant effects on the performance and uncertainty estimates of the estimation system. Therefore, we are interested in estimation approaches that can self-tune to the uncertainty characteristics of the inputs, providing more accurate state and uncertainty estimates.

3. Robust estimators that can detect and appropriately handle conflicting or erroneous data. While uncertainty in the inputs is generally expected with estimators, minimum squared error estimators are significantly affected by outliers. Estimators that recognize erroneous inputs and discard them in principled ways are of significant interest.

The goal of this research is to enable theoretical or applied improvements to estimation systems, with an emphasis on one or more of the areas described above.

SF.35.01.B7518: Printed, Flexible Microwave Circuits

(937) 713-8854

This research focuses on the use of non-traditional fabrication techniques, such as additive manufacturing, for the advancement of microwave and RF circuits. We are exploring the creation of devices that combine traditional fabrication techniques with non-traditional fabrication techniques. The performance of these devices will be compared to that of state-of-the-art devices fabricated by traditional means. The development of improved devices for use in microwave circuits (including, but not constrained to, inductors, capacitors, transistors, and antennas) is critical in moving beyond the end of Moore’s Law.

This proposed project will explore the use of non-traditional fabrication techniques, such as additive manufacturing, for the advancement of microwave circuits. The use of additive tools and processes, such as ink jet printing, aerosol jet printing, nano-imprint lithography, and nScrypt printing, should be used along with traditional fabrication techniques in this project. Existing procedures for microwave device testing will be used to analyze and compare these devices.

Potential non-traditional materials may include oxides, graphene, CNTs, organic polymers, and nanoparticles. Our in-house research involves device modeling, design, fabrication, testing, and the comparison of printed devices with those fabricated using more traditional techniques.

SF.35.01.B7606 : Multi-agent Sensing Systems

(937) 713-8184

The primary objective of this research is to develop and demonstrate the capability of multi-agent systems to sense an environment and build a semi-coherent and synchronized model of that environment. In particular, we are interested in improvements in two primary areas described below.

First, while there has been significant research in the area of distributed sensing, many practical examples that have been put forward deal with very simple models of the environment. One example is a sensor network detecting the temperature of an area. Because temperature is a single number and highly correlated over space, building a global model is relatively straight-forward. Imagery sensors (cameras), on the other hand, collect huge amounts of data making the communication of this data to all agents in the network problematic. In addition, as the network grows, keeping a full-resolution global model precisely synchronized across all nodes in the network also becomes impractical. Therefore, a hierarchical, semi-synchronized model may be required. Research into generating and maintaining the global model across a distributed multi-agent system when the global model is very large is a significant research problem for multi-agent sensing systems.

Second, when sharing data across agents in a network, overcoming the track-to-track correlation problem while still improving on the performance of any one sensor is fundamental to achieving distributed data fusion (DDF). However, most approaches that overcome the track-to-track correlation problem provide very conservative estimates of the fused data uncertainty. Research into DDF techniques that achieve more accurate estimates without becoming over-confident is of interest when designing multi-agent sensing systems.

SF.35.01.B7634 : Dual-System Based Formalism for Data to Decisions

(937) 713-8525

AFRL requires innovative approaches to the problem of developing robust subjective representations of sensory data to apply to many Data to Decisions (D2D) problems. Systems that rely on creating an objective representation of the world are prone to fragility as a result of sensor degradations and dramatic differences in input. These systems are characterized by the attempt to capture attributes of the environment under consideration in a physically accurate representation. In contrast, nature has developed a dual system approach that is able to robustly deal with degradation of sensors and incomplete information. System 1 is fast and reflexive in nature, while System 2 is slow and logical. We seek an implementable mathematical formalism that can model these two systems along with their blending--allowing for learning and decision-making based on a subjective representation that is not tied to maintaining fidelity with physics-based reality. Application areas include D2D domains such as target identification and tracking, sensor management, sensor fusion, cyber, and ISHM. Publication of the resulting work (both on ATRPedia and in public sources) is expected, along with the delivery of any source code developed.

SF.35.01.B7635 : Discovery for Difficult Targets

(937) 713-8290

AFRL is interested in discovering new ways to assemble exploitable difficult target signature attributes from the layered-sensing construct--explicitly, from field-able sensors into products indicative of object type or purpose. Targets of interest include dismounts and in particular, vehicles. Understanding and organizing target data is the first step toward this goal. The goal of this research is to exploit data from Full Motion Video (FMV), infrared (IR), LiDAR/LADAR, Hyperspectral, and Polarimetric IR sensors, individually or in concert, to determine what measurable characteristics, or combinations of measurable characteristics, can be used to classify entities in the data. Once characteristics are identified that allow for classification, sensed data can be tailored to capture the measurements necessary for exploitation and identification. This effort may include a data collection using fixed sensors from a standoff range (greater than one kilometer). In addition to publications (both on AFRL's internal ATRPedia and public venues), delivery of documented source code will be expected.

SF.35.01.B7636: Automated Tracker Tuning

(937) 713-8075

Tracking systems operate in a complex environment, connect to multiple sensors and data sources at varying sample rates, handle a diverse set of targets, and all in real time. Typically, adding a new sensor source requires that the tracking engine needs to be tuned to adjust to the characteristics (measurement types including kinematic and feature/classification/identification information, false alarms and clutter, revisit rate, accuracy, biases) on the new measurements. Additionally, the tracking algorithms have many parameters that impact the overall performance, such as association gates and detection thresholds, maximum prediction times before preventing associations, and track initiation and termination policies.

The goal of this effort is to develop algorithms and provide an architecture that allows automated trackers to adapt to the implicit information that is contained in the input data streams by selecting appropriate algorithms and tuning these algorithms in order to produce a complete and accurate picture of the battlespace. At a higher level, the operator (not assumed to be a tracking expert), would simply designate either truth or good/bad tracks as training samples for use in automatically tuning the tracker. Initial focus will be on image-based sensors (FMV or WAMI), but with extensibility to other sensor modes (e.g., radar). Sensor data will include motion video in the following modes: color (VIS) and infrared (IR). In addition to publications (both on ATRPedia and public sources), delivery of documented source code will be expected.

Keywords:

Target tracking; automated tuning

SF.35.02.B0220: Advanced Antenna Technology

(937) 713-8962

Research opportunities exist in the area of high-gain and multibeam antennas to support Air Force air- and spaceborne radar systems. We are particularly interested in wideband (>1 octave) and multiband systems, and in developing both new antenna designs and new efficient analysis methods. This applies to directly radiating planar and conformal arrays, as well as array-fed reflector and lens configurations, which offer the potential for an electrically scanned, high-gain beam at low cost.

A final topic centers on computational electromagnetics for electrically large bodies. We need to improve both frequency and time domain methods, which eventually will permit us to numerically analyze large finite planar and conformal arrays, including mutual coupling and edge effects on large complex platforms, possibly of exotic nonconducting materials including metamaterials.

(937) 713-8985

Our interests include electro-optic, magneto-optic devices, components, sensors and focal plane arrays operating in the near infrared to the millimeter wave spectrum. Our current research focuses on improved signal detection, polarization control, or other enhancement to photodetectors and focal plane arrays operating in the mid-wave to long-wave infrared with specific interest in multispectral sensing. For example, we are studying the use of metamaterials and plasmonics to enhance the performance of quantum dot photoconductors and focal plane arrays for multispectral sensing. We are using the metamaterial and plasmonics enhancements to reduce the background radiation and increase the selectivity of the photodetectors and focal plane arrays. The work involves experimental investigation as well as modeling of the photodetectors and focal plane arrays. Our facilities include high-end workstations and personal computers, design and characterization capability in the near to long wave infrared. Our characterization capability includes a mid to long wave FTIR, a femtosecond laser tunable from 1 to 20 micrometers for spectral response, photocurrent, dark and noise current measurement setups, and a Photoluminescence measurement setup with sample temperature control form 15 to 300 K. There is access to a full microelectronics cleanroom with nanofabrication capability like high resolution electron-beam lithography and nano-imprinting. There is also access to a high performance computing center, and in-house epitaxy and materials synthesis.

(937) 713-8940

Research opportunities exist to develop analytic and numerical methods, in both frequency and/or time domain, for predicting electromagnetic and optical wave propagation and scattering from surfaces and particles of general shape, size, and composition, with random and/or periodic distributions. The statistical nature of the scattering and its dependency on frequency and polarization are significant. Methods for predicting scattering include but are not limited to high-frequency diffraction, surface-integral-equation, volume-integral-equation, transform-iterative, and finite-difference or finite-element techniques.

We emphasize the accurate determination of the complete scattering characteristics of multiwavelength, second-generation canonical shapes (to act as benchmark and calibration solutions for general computer codes and bistatic cross-section measurements) and the diffraction at all angles of incidence and observation from antennas and scatterers. An additional interest is the relationship between the statistical nature of the scatterer and the properties of the scattered field. To complement the theoretical effort, we are developing both near- and far-field techniques to measure the radiation and scattering characteristics of arbitrary antennas and scatterers.

SF.35.02.B5355: Integration of Knowledge and Sensor Data for Intelligent Actions

(937) 713-8941

Research opportunities exist in the area of advanced methods for integrating knowledge and data coming from a variety of sources and sensors with the goal of developing intelligent systems capable of extracting actionable information from data and knowledge. Sensor development and data extraction is only one part of enabling the decision support processes. Discovery and disambiguation of the system of interacting agents coordinated within the set of goals is the essence of information construction required for successful decision-making. Between data and actions there are processes of information extraction based on knowledge. Networks of knowledge, interwoven with intentional systems of goal-oriented agents, ought to account for the available options in decision-making based on data, knowledge, phenomenology, and computational processes.

Knowledge includes physical models of sensors, wave propagation and scattering, statistical models of object properties, dynamical models of motion, linguistic text models, semiotic models of meaning, and cultural models of human behavior in a society of interest. Corresponding to the available knowledge, the models might be detailed or approximate, reflecting precisely known physical laws or uncertain intuitions about undiscovered phenomena or human nature. The integrated functioning of an intelligent system is not a one-time deal but a continuous loop of operations in which sensors and data collection are directed based on the current-moment results; models and actions are continuously refined.

The relevant systems have substantial affinity with the known mechanisms of brain and intelligence of living creatures. Whereas, the past algorithms combining knowledge and data often encountered prohibitive combinatorial complexity, the mind can do it. The mind avoids combinatorial complexity by combining conceptual understanding with emotional evaluation. We hope to develop algorithms utilizing non-combinatorial measures of similarity between models and data, resembling affective-emotional capabilities of the mind in combination with modeling-conceptual capabilities.

Biology suggests that intelligent systems are evolving systems. Evolution is a desirable property of the AF systems, so that they improve with experience, rather than become obsolete. Genetic evolution inspired the development of genetic algorithms. Other evolutionary mechanisms suggested by cultural evolution operate faster than genetics. We are interested in evolving network-centric sensory systems inspired by biological evolution of communication and language systems.

SF.35.02.B5790: Phenomenology-Based Adaptive Radar Signal Processing

(937) 713-8567

Research opportunities exist in physics and phenomenology-based adaptive signal processing methods for enhanced radar target detection and estimation. Classical adaptive signal processing methods for radar rely on the formation and inversion of a sample covariance matrix. However, nonstationary reflectivity properties of the scanned areas, dense target environments, and strong clutter discretes tend to introduce heterogeneities in the training data for covariance estimation. These tend to have a deleterious impact on detection and false alarm performance. Furthermore, as the dimensionality of the problem increases, the training data support for forming the covariance matrix and the computational cost of the matrix inversion are prohibitively high. To address these issues we seek to exploit a priori information from the scattering physics or phenomenology underlying a given scenario. For example, in many instances clutter can be viewed as the resultant of the scattered power from a small number of strong interference sources, thus rendering it low rank. This information can then be advantageously used to reduce the training data support and computational cost of the resulting adaptive processing algorithm. The problem of target detection is further complicated by the presence of a large number of nuisance parameters. These effects are exacerbated by systems and environmental considerations pertaining to the operational scenario. We seek novel approaches based on either a priori knowledge of the clutter scenario or on principles of invariance for this problem with a goal to maintain a constant false alarm rate and achieve robust target detection performance. Development and performance analysis of MIMO radar signal processing algorithms for the above described scenarios is of particular interest.

SF.35.02.B7397: Sensors Aboard Hypersonic Vehicles

(937) 713-8948

Hypersonic flights lead to high temperature flows, air dissociation, and cumulative heating of air-frames. Consequently the performance of all on-board sensor systems such as GPS, telemetry, communication, command and control, radar, ladar, and electro-optical sensors are all adversely affected to varying degrees by the hypersonic environment. Further, the dynamic range of parameters that characterize the environment is quite large and is strongly influenced by many factors including altitude, velocity, duration of flight, geometry of the vehicle, airframe, and heat-shield material. For instance, the electron density can vary by several orders during the course of a trajectory. Hence, sensor systems encounter a variety of situations. Some of the issues encountered include signal attenuation, communication blackout, signal distortion due to turbulent flow, radiation from heated optical windows, and emission from hot flows. Communication blackout although old is still a problem and is encountered when the signal frequency is well below the plasma frequency. An adaptive sensor system which uses a diagnostic tool to sense and adaptively match to the environment will be desirable. Even in the case when the signal is above the plasma frequency the boundary layer flow can be dispersive, inhomogeneous, fluctuating, and lossy. This poses challenges to wideband RF system using conformal arrays. With arrays we also face the problem of mutual coupling and impedance mismatch effects on beam forming. Moreover, the signal transmitted from the vehicle may be sufficiently intense to initiate nonlinear processes in the flow. The rapid maneuvers and high velocity place limitations on the integration time of the processing algorithms of the receivers. Although optical sensors are not similarly affected by hypersonic flow as RF sensors they have their own share of issues. The hot window can radiate at infrared frequencies and the hot flow fields can emit and absorb at optical frequencies thereby seriously affecting the optical and EO/IR sensors on board. Two major problems of concern are beam pointing error and wave front distortions. We are particularly interested in assessing the impact of environment on spectral measurements and imaging. Research opportunities exist in the analyses and mitigation of the above-mentioned issues confronted by sensors aboard hypersonic platforms.

SF.35.02.B7398: Scattering and Propagation in Complex Environment

(937) 713-8948

Our primary interests are (1) the statistical models for radar environment such as terrain, ocean, hilly region, forest, atmosphere, ionosphere, and urban region; and (2) relation of the statistical properties of the scattered signals with that of the environment model.

Topics of interest include waves in random media (discrete and continuum models), radiative transfer theory and remote sensing, scattering from randomly rough surfaces, polarimetric scattering, inverse scattering and parameter retrieval from measured data, physics-based models for scattering from terrain and ocean, scattering from media with space-time fluctuations, monostatic and bistatic models for radar clutter, combined random media and rough surface scattering, spectral density of scattering from ocean surfaces, scattering and propagation of radar signals through turbulence in atmosphere and ionosphere, and models for subsurface sensing. Most studies in the literature on these topics are on the derivation of the average scattering coefficients or propagation constants. However, we are interested in more detailed statistics such as probability density function and spectral density of the scattered signals. Often the signals will be of wide bandwidth, so we are interested in the characteristics of scattered signals over a wide range of frequencies. We are also interested in studies on the scattering of targets embedded in complex environment and polarimetric techniques for detecting such targets. The targets may be stationary, mobile, or fluctuating. Of particular interest is the location and imaging of targets embedded in a complex environment.

(937) 713-8714

Light sources and detectors are essential components of infrared (IR) sensing systems. However, many other optical beam control components such as diffractive optical elements (DOE), spatial light modulators (SLM), optical micro-electro-mechanical systems (MEMS), optical phased arrays (OPA), optical filters, optical isolators, optical limiters, and other devices are also required. For the visible spectrum (0.4-0.7 micron), near infrared (0.7-1.4 micron), short-wavelength infrared (1.4-3 micron), there are many available commercially-off-the-shelf (COTS) devices and technologies. However, for the mid-wavelength infrared (3-8 micron) and long-wavelength infrared (8-15 micron), the choice of the optical beam control devices and technologies is limited. Therefore, we continue searching for innovative beam control technologies for IR sensing applications. The number of applications is virtually unlimited: laser detection and ranging (LADAR), infrared countermeasures (IRCM), infrared scene projectors (IRSP), multispectral and hyperspectral imaging (MSI and HSI) systems, and so on. The demand for new enabling technologies and solutions is growing.

[4] Anisimov, I. et.al., “Infrared Dynamic Scene Projectors: Technical Challenges and System Requirements”, 2016 GOMAC Tech Conference (Unlimited distribution version of the paper is available from the author upon request).

SF.35.12.B1101: Fully Adaptive Radar

(937) 713-8567

Research opportunities exist in physics and phenomenology-based adaptive signal processing methods for enhanced radar target detection and estimation, tracking and classification involving closed loop radar operation. The onerous challenges of harsh environments, difficult targets, and a rapidly shrinking electromagnetic spectrum necessitate a systematic treatment for developing closed-loop radar operation. The concept of fully adaptive radar (FAR) seeks to exploit all available degrees-of-freedom on transmit and receive in order to maximize target detection, tracking and classification performance. This area has received increased interest in recent times and builds upon a rich history of prior research. Of key importance is the concept of closed loop radar operation via feedback. Specifically feedback from the receiver and tracker to the transmitter for guiding the next illumination to better concurrently detect, and track targets of interest in computationally demanding and training data starved scenarios is required. A first step is the development of the feedback signal from the receiver and tracker to the transmitter via prescribed metrics such as mean squared error, entropy, or mutual information. The next step is to develop analytical and computer simulation methods for determining the detection, tracking, and classification performance with respect to single and multiple radar waveforms. Furthermore, due the large number of degrees of freedom, the number of unknown nuisance parameters incurs a substantial increase. Consequently the curse of dimensionality prevails. Novel approaches for overcoming this issue are of considerable interest. Concepts of machine learning can be brought to bear in a powerful manner in this context. Relevant performance metrics include the tracking error and computational cost. Extension of this approach to handle distributed and MIMO radar performance must be undertaken. Performance validation for both single and distributed radar needs to be analyzed using simulated and measured data sets.

SF.35.13.B0921: Resonance-Based Chemical/Biological Sensors

(937) 713-8920

The major objectives of this work are to design and fabricate plasmonic and micro-/nano-resonant structures for optical chemical/biological sensing applications. Examples of such structures may include metallic nanoparticles, nanoantennas, plasmonic metamaterials, or resonant microcavities. Theoretical models and computational simulations will be developed for these structures to describe the electromagnetic behavior as well as chemical/biological sensitivity of these devices. The resulting fabrication techniques and modeling methods will lead to new technology for devices that can be tailored for specific analytes for chemical/biologic detection schemes. The developed methods and designs will also provide the foundation for techniques to develop new biorecognition elements and surface functionalization chemistries that are key to the success of these systems. It is anticipated that the modeling/fabrication/characterization efforts will be iterative towards the development of a highly sensitive microresonator-based biosensing platform that is robust and amenable to multiplexing arrays.

SF.35.14.B0808: Printed Electronics and Photonics

(937) 713-8855

This research focuses on using novel fabrication techniques such as ink jet and aerosol jet printing and nanoimprint lithography to print electronic and photonic circuit and device elements. Focus will be on novel materials such as polymers, CNTs, graphene, etc. and on flexible substrates. In-house research involves device and material fabrication, characterization and testing of fabricated structures. Current areas of interest are in field effect transistors and mid-wave IR detectors.

SF.35.14.B0809: Micro-Mechanical Oscillators

(937) 713-8851

This research seeks to push the performance of micro-mechanical oscillators for applications including the generation of microwave signals, diverse waveforms, and entangled photons. We are currently characterizing resonators made out of a novel material which seeks to improve on what has be traditionally demonstrated. Opportunities exist to contribute to theory, experiment, and/or simulations depending on background and interest level.

SF.35.14.B0810: Injection-Locked Semiconductor Lasers

(937) 713-8851

This research focuses on studying the injection locking of quantum-well and quantum-dot semiconductor lasers primarily in order to generate narrow-linewidth tunable microwave signals. Here different topologies as well as more fundamental issues (such as the suppression of amplitude and frequency fluctuations) are of critical interest and currently being investigated. Depending on background and interest level opportunities to contribute to one or more of the different areas we are investigating including theoretical studies, experimental work, and/or numerical simulations exist.

SF.35.14.B0811: Polycrystalline YAG Fiber Characterization

(937) 713-8851

This research seeks to demonstrate a viable Polycrystalline YAG fiber for use in amplifier and laser applications. Opportunities exist primarily in contributing to the characterization of these fibers but also in improving these AFRL-made fibers and working toward the goal of demonstrating a viable laser source using these fibers.

(937) 713-8941

There has been an increasing emphasis in research on autonomous information fusion, sensemaking, and the challenges they presents. The fact is that effective autonomous fusion and sensemaking of visual information is a very complex and surprisingly difficult task to accomplish. Effective autonomous modeling and understanding of many real word situations and scenes also requires complex hierarchical representation of the sensor information. Data in different space and time scales and modalities is coming from a variety of sensors and other types of information collection methods with different limitations and levels of plausibility. The meaningful information could be extracted after analyzing the hierarchy of multiple facts and concepts. For typical complex learning algorithms, especially multi-layered neural networks, the processes in the inner layers are usually not transparent and have no clear relationship with the low level patterns they recognize. In contrast to current machine learning algorithms, a successful human learning experience produces a clear explanation for the facts or hierarchy of linked concepts that have clear meaning and can be "recycled" in other learning and explanatory processes. Perhaps the absence of clear associations with meaningful concepts in the machine decision steps cause resistance toward acceptance and trust in the results produced by machine learning algorithms.

We are trying to formulate a transparency principle for hierarchical machine learning algorithms which can make result inferences produced by the algorithm more trustworthy and understandable by humans. Hence, it is our hope that this will lead us toward better synergy and cooperation with machines.

Keywords: unsupervised learning, hierarchical learning, visualization

SF.35.16.B0001: Single-crystal Silicon Carbide Resonant Microsystems

(937) 656-4634

This research seeks to expand the state of the art of single-crystal silicon carbide (3C, 4H, 6H, etc.) resonant microsystems exploring novel device concepts and integration of MEMS devices with solid-state electronics. The intent is to expand resonant system performance of RF oscillators and filters under high temperature environments. In-house research involves modelling and simulation of device performance, device fabrication, and characterization.

SF.35.16.B0002: Optical Properties of 2D Materials:

(937) 713-8927

Atomically thin transition metal dichalcogenide materials, with their remarkable optical and electronic properties, are proving to be promising candidates for quantum based photonic integrated circuits. Several research groups have recently demonstrated single photon emission from two dimensional tungsten-diselenide (WSe2) [1,2,3,4], with second order correlation function values well below 0.5 [1]. The origin of the single photon emission comes from defect states in the material, although little is currently known about the nature of these defects. It is plausible to assume that such localized emitters exist also in other transition metal dichalcogenides (TMDCs). In order to fully realize the potential of these materials, a more detailed study of the optical and electronic properties of these defect states is required. We are studying such defect states in a variety of two dimensional materials, such as MoS2, MoSe2, MoTe2, WS2, WTe2, both theoretically and experimentally. In particular, we are going to investigate whether the operating temperature of the single-photon source can be increased above 10 K, and whether the emission of the single photons can be triggered on demand for the potential use in quantum information technology. One of the main advantages of 2D materials for single-photon sources is that defects can be created by means of standard lithography methods. In addition, while single photons from 3D materials need to travel through the host media with a large refractive index, single photons can be extracted from 2D materials much more efficiently.

(937) 713-8927

Investigations are underway to exploit orbital angular momentum (OAM) of light with a focus towards quantum based photonic integrated circuits. Current OAM communication links utilize liquid crystal based spatial light modulators which are relatively bulky and expensive. We are exploring alternative, chip scale platforms for creating integrated OAM transmitters and receivers with an eye towards information transfer with improved security and with increased robustness to transmission through turbulence. Novel methods of incorporating active tuning into an OAM photonic integrated circuit will provide increased functionality of the devices. Design, numerical modeling, fabrication, and characterization are being pursued, as well as exploration of potential algorithms and protocols for quantum information and quantum processing.

SF.35.16.B0004: Aspects of Robust Sensing via Cognitive Radar

(937) 713-4299

A cognitive radar (CR) framework is defined by its exploitation of feedback, memory, and prediction on multiple scales or levels in order to enhance the traditional adaptive/fully adaptive/knowledge-aided radar frameworks. In addition, a cognitive approach often features coupled or jointly designed system architectures. These features increase the computational and design complexity of a given system in order to increase the adaptivity and robustness of the sensor(s). Therefore, care must be taken to properly mitigate the risks of a coupled design featuring feedback (e.g. stability, learning saturation, etc.). However, such a design methodology offers the potential to adapt to a dynamic environment, spectral or otherwise, in a robust, efficient manner.

Our interest is in applying the CR framework to enable robust sensing in a distributed, netted cognitive radar network (CRN). As such, we are interested in designing fully adaptive radar networks that can maintain sensitivity in the face of degraded sensors, intentional and unintentional RFI, heterogeneous clutter, as well as numerous other challenging scenarios. The distributed nature of the network also requires adaption to the difficulties inherent in multistatic sensing (e.g. multistatic clutter, waveform orthogonality/separability, communication/collaboration requirements, etc.). Finally, these networks should show the capability to learn and adapt to unforeseen circumstances based on past experience.

SF.35.16.B0006: Metamaterials, Plasmonics and Photonics for Novel and Enhanced Sensing

(937) 713-8916

Research opportunities are currently available for the theoretical and experimental investigation of novel sensing schemes. Optical metamaterials, plasmonics and photonics technologies will be utilized to provide enhanced sensing that could ultimately be the backbone of the next-generation Detectors and Focal Plane Arrays (FPAs). The wavelength regimes of interest are short-wave, mid-wave and long-wave infrared. We are interested in the study of novel sensing mechanisms that would lead to more sensitive and lower noise devices. The study could include any aspect of the design and synthesis of the materials to the architecture of the device. The study at the very minimum should include simulations with the quantitative proof-of-principle, but ideally experimental demonstration should be included through fabrication and characterization. Simulation, Fabrication, and Characterization facilities will be provided.

SF.35.16.B0007: High Performance Small Telescope Sensing

(937) 713-8795

Comprehending the physics-based relationships involved in electro-optical propagation and object signal characterization, parameters such as color reflection and emissivity offer a multidimensional representation of object characterization, and in the case of complex non-resolved signals of interest, light curves. This can also be described in terms of information content and signature prediction. Innovations in active and passive receiver architectures and atmospheric propagation algorithms will be required as well as novel methods for characterizing signals as a function of light curve predictions. The design of experiments using physical modeling and simulation tools is desired in developing the EO active and passive non-resolved characterization methods, from visible to infrared, with appropriate statistical analysis. The formulation of EO laboratory and observatory experiments for prototyping of small telescope optical subsystems integrates with active laser-assisted assemblies for future defense applications. Recently completed research has revealed opportunities to develop nontraditional small telescope-based architectures, which bridge active and passive sensing technologies as a multidisciplinary area to address fundamental limitations (e.g., BRDF, atmospheric turbulence, thermal noise, Nyquist/Shannon theorem limitations, etc) to more efficiently predict a signal and collect required data for non-resolved object characterization. Our long-term research goal is to enable advanced small telescope solutions capable of supporting space object characterization under humid, continental climate and deep turbulence regimes.

SF.35.17.B0001: Secure Bio-Inspired Computing For Autonomous Sensing

(937) 713-8941

The goal of the proposed efforts is to discover inconsistencies and monitor integrity of sensors data, situation models and goals formulated by human operators. The approach is based on developing two level processing systems architecture under the dual-process cognitive framework using bio-inspired embedded computing system integrated with a cognitive-neuromorphic data-to-decision algorthms that delivers a set of autonomous sensing capabilities for Air Force ISR missions in contested and A2/AD environments.

(937) 713-8989

The focus of this lab task is measuring the electrical and optical properties of α-Sn and α-SnGe alloys to assess their suitability for electrical and optical devices. Tin is a group-IV element that can assume the diamond crystal structure (the α-phase) and become a zero-gap semiconductor with a band gap opened with strain. Moreover, strained α-Sn has been shown to be a topological insulator, a newly discovered class of materials that have an insulating bulk but metallic, spin-polarized surface bands. These properties make α-Sn a candidate for several applications, such as high-speed, low-power electronics; long-wavelength IR detectors; spintronics; and, quantum computing. Our technical approach is to synthesize α-Sn films by molecular beam epitaxy (MBE) on nearly lattice-matched substrates to produce highly crystalline films in well-defined strain-states and, consequently, adjust the band gap and associated electronic properties. We measure these properties using magneto-transport and optical methods.

We require expertise in the modeling of band-structure of narrow-gap semiconductors and the interpretation of multi-carrier transport measurements. We also require expertise in the modeling of far IR optical measurements.

(937) 713-8740

The goal of this research project is to develop Si1-x-yGexSny for sensor applications: 1) remote sensing applications such as IR countermeasures, remote hyperspectral imaging, and high sensitivity chemical/biological weapons detection; 2) as a potential broad NIR, MWIR, and LWIR detector material for use in laser RADAR; 3) as a CMOS-compatible material for development of electro-optic integrated circuits (EOIC) including smart pixels for advanced focal plane arrays (FPAs); and 4) for free-space optical communication. The large size difference of these group IV elements presents unique challenges which require the development of a new approach to allow synthesis over a broad range of composition. Achieving this goal will require substantial effort in process development. Investigation of the gas phase chemistry and associated growth kinetics will provide a fundamental understanding of the surface physics and reaction chemistry involved in this process. Synthesis will be closely coupled with characterization of the basic structural, surface, electrical and optical properties of the resulting films to inform the growth optimization process.

(937) 713-8738

When military planes, spacecraft, and ballistic missiles travel at hypersonic speeds at Mach 5-10, and envelop hot ionized air develops around them. This plasma sheath acts as a mirror against electromagnetic signals under most conditions, cutting off RF signals with anything outside the vehicle. A Fractal antenna could help these vehicles keep in contact with ground and air control, despite the sheath of plasma surrounding the vehicles. A fractal antenna is an antenna that uses a fractal or self-similar motif to maximize the length, or increase the perimeter and can received or transmit electromagnetic radiation within a give total surface area. Investigate the surface area (2D) fractal antenna and volume (3D) fractal antenna to optimize the radiation prorogation.

SF.35.17.B0005: Cognitive Captioning for AF Data

(937) 713-8202

Deep learning techniques are currently producing state of the art (SotA), results in common image and video exploitation tasks. Of particular interest are existing image and video captioning systems. Such results are attained through the use of great quantities of representative data for training consisting of pairs of imagery/video and human-written descriptions.

To date, the data that has been utilized is public in origin. Both the motivation and goal of this effort is to ascertain the performance of these existing SotA tools on AF mission-relevant data and, consequently, improve on the SotA. This particular effort will apply deep-learning approaches to a combination of data-types (e.g. imagery and text) to learn relationships between representations, ultimately producing accurate and improved semantic descriptions of scenes observed from AF-relevant platforms.

Publication of the resulting work (both on the sensors directorate's internal ATRPedia and in public venues) is expected, along with the delivery of all source code developed.

SF.35.17.B0006: Deep Generative Models for Closed Loop Sensing

(937) 713-8578

The principal focus of current deep learning research has relied on supervised learning where an extensive number of labeled training examples (many 100s per class) are required. However, AFRL is interested in settings where knowledge representations can be developed from sensed data that can be shared across multiple related sensing tasks and which are robust to unseen mixtures of nuisance parameters. For such representations disentanglement of the causal factors in measured data is required. A number of unsupervised learning approaches have been proposed in the literature for learning these representations to include variational auto-encoders and generative adversarial networks. The objective of this research is to explore such unsupervised approaches for learning representations for closed loop sensing. Publication of the resulting work (both on the sensor's directorate internal ATRPedia and in public venues) is expected, along with the delivery of all source code developed. Keywords: unsupervised learning, deep generative models, attention, active vision.

SF.35.18.B0001: Applying CRISPR Immune System Methodologies to Embedded System Malware Detection and Response

(937) 713-8054

This proposed research project focuses on exploring adaptive immune systems found in bacteria and archaea and applying the underlying methodologies, as appropriate, to develop a cyber immune system targeting computer malware on embedded systems. Recently, an adaptive biological immune system composed of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) together with CRISPR associated (Cas) proteins found in bacteria and archaea has been used to perform targeted genetic editing experiments to repair/replace human and animal genes known to cause disease. An open question is whether the underlying biological methodologies and mechanisms that make up this immune system could also be used to recognize and respond to computer malware. The focus of this research project is to explore the three phases associated with CRISPR immune systems, namely (1) adaptation, (2) expression, and (3) interference, to determine its applicability to developing cyber immune systems.

Research in the first phase should lead to a comprehensive understanding of the mechanism the CRISPR immune system uses to discriminate host DNA from foreign DNA (i.e., self vs. non-self) in order to apply the underlying process or approach to distinguish computer malware from the host software in which it is embedded. Research focusing on the second phase includes developing bio-sequencing analysis programs that can recognize the previously stored foreign viral DNA sequence in a software application that could contain embedded malware. Finally, research focusing on the third phase should investigate an approach to malware response that involves precise genetic editing of the viral DNA to destroy or disable the virus, in much the same manner as genetic engineers and biologists are using CRISPR to correct genetic defects that cause disease in humans and animals. The desired end-goal of the project is to develop a software and/or hardware prototype that uses the underlying mechanisms found in CRISPR to perform malware detection and response.

SF.35.18.B0002: Adaptable Cyber Security

(937) 713-8054

The ability to sense, learn, and adapt to cyber security threats is required to provide mission assurance to the warfighter. This project will focus on research and development of one or more key enabling technologies necessary to build self-protecting cyber security systems, namely: (1) the development of cyber sensors that will identify architectural or implementation defects in the target platform, including, but not limited to developing active sensor probes to accelerate contextual learning for use in subsequent adaptive response, (2) the ability to determine access to discovered defects (e.g., via trace-based analysis) and associated triggering mechanisms , and (3) the ability to respond to unanticipated attacks by providing self-adapting mechanisms, including the ability to repair or replace defective software or firmware, or to disrupt malware triggering mechanisms in order to provide resiliency to ongoing attacks. The end-goal of this project is to develop a software or hardware-based proof-of-concept that demonstrates one or more of the above capabilities.

SF.35.18.B0003: Growth and characterization of two dimensional materials and heterostructures

(937) 713-8929

Our research focuses on the development of promising two dimensional (2D) electronic materials and their heterostructures for the next wave of nanoelectronics. The wide variety of available 2D materials gives a full tool box of materials properties to explore. We are actively developing growth, fabrication and characterization methods of 2D hBN, graphene, phosphorus materials, heterostructures and devices. Research emphasis is 1) to develop methods, models, and understanding of vapor phase growth of these atomically thin van der Waals layers and 2) to study the effects of interlayer interactions between 2D and 3D materials on electronic transport and optical properties. A combined experiential and theoretical approach to study growth and properties will help realize the fully potential of these materials. Our laboratory operates several CVD and MOCVD reactors for growth of 2D layered materials. These growth techniques are complemented by a variety of structural, optical, and electrical characterization tools, as well as, fully equipped nano fabrication facilities.

SF.35.18.B0004: Scaled Stellar Interferometry Laboratory Research

(937) 713-8798

Comprehending the physics-based relationships involved in optical stellar interferometry in order to perform scaled laboratory experiments investigating novel concepts on topics such as fiber based beam relay effects, beam combination for fringe detection, atmospheric mitigation and interferometer component risk reduction research. The design of experiments using physical modeling and simulation tools is desired in developing methods for investigating novel concept research in a scaled laboratory environment. The formulation of optical interferometry experiments will be applied to future defense applications. Recent technology advancements in fiber design and optical sensor technology have revealed opportunities to investigate new component choices applied to long baseline optical interferometry not previously studied which could yield low cost improvements to existing long baseline optical interferometer design. Our long term research goal is to enable low cost solutions to optical stellar interferometer component design that support defense applications in space object characterization and space situational awareness.

(937) 713-8529

Multimodal machine learning aims to build models that can process and relate information from different modalities such as EO, IR, Hyperspectral and RF. In recent years, machine learning has been successfully applied to multimodal learning problems, with the aim of learning useful joint representations in data fusion applications. In this effort, we are interested in developing the state of the art machine learning algorithm which will include but is not limited to deep learning based approaches to address the challenging problem the US Air Force faces in the realm of Multi-INT Aided Target Recognition (AiTR), and publish our findings in peer reviewed Journals and conference proceedings. Delivery of any source code developed is expected.